Automatic tuning of agent-based models using genetic algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3891 LNAI, Issue , 2006, Pages 41-57

  Calvez, Benoît ^a   Hutzler, Guillaume ^a  

^a UNIVERSITÉ D EVRY VAL D ESSONNE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; GENETIC ALGORITHMS; OPTIMIZATION; PARAMETER ESTIMATION; SOFTWARE AGENTS; TUNING;

AGENT BASED SIMULATION (ABS); AUTOMATIC TUNING; FOOD-FORAGING; GLOBAL DYNAMICS;

MULTI AGENT SYSTEMS;

EID: 33745590839     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11734680_4     Document Type: Conference Paper

References (12)

1. Sallans, B., Pfister, A., Karatzoglou, A., Dorffner, G.: Simulation and validation of an integrated markets model. J. Artificial Societies and Social Simulation 6(4) (2003)
2. Tisue, S., Wilensky, U.: Netlogo: Design and Implementation of a Multi-Agent Modeling Environment. Proceedings of Agent 2004 (2004)
3. Brueckner, S., Parunak, H.V.D.: Resource-Aware Exploration of the Emergent Dynamics of Simulated Systems. AAMAS 2003 (2003) 781-788
4. Fehler, M., Klügl, F., Puppe, F.: Techniques for analysis and calibration of multi-agent simulations. In Gleizes, M.P., Omicini, A., Zambonelli, F., eds.: ESAW. Volume 3451 of Lecture Notes in Computer Science., Springer (2004) 305-321
5. Jin, Y.: A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing Journal (2003)
6. Cant-Paz, E., Goldberg, D.E.: Efficient parallel genetic algorithms: theory and practice. Computer Methods in Applied Mechanics and Engineering 186 (2000)
7. Jin, Y., Olhofer, M., Sendhoff, B.: A Framework for Evolutionary Optimization with Approximate Fitness Functions. IEEE Transactions on Evolutionary Computation 6(5) (2002) 481-494
8. Beyer, H.G.: Evolutionary Algorithms in Noisy Environments: Theoretical Issues and Guidelines for Practice. Computer methods in applied mechanics and engineering 186 (2000)
9. Goldberg, D.E., Deb, K., Clark, J.H.: Genetic algorithms, noise, and the sizing of populations. Complex System 6 (1992)
10. Beker, T., Hadany, L.: Noise and elitism in evolutionary computation. In: Soft Computing Systems - Design, Management and Applications. (2002) 193-203
11. Amar, P., Bernot, G., Norris, V.: Modelling and Simulation of Large Assemblies of Proteins. Proceedings of the Dieppe spring school on Modelling and simulation of biological processes in the context of genomics (2002) 36-42
12. Takagi, H.: Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation. In: Proceedings of the IEEE. Volume 89., IEEE Press (2001) 1275-1296